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OB360

AI Agents & Multi-Agent Systems

Design and implement governed AI agents, coordinated workflows and enterprise tool integrations.

Discuss your AI initiative

Definition

Coordinate agents, tools and people around real enterprise workflows.

In brief: OB360 designs and builds AI agents and multi-agent systems for enterprise workflows. Each agent has explicit responsibilities, approved tools and escalation paths; an orchestration layer routes work between them; and people approve actions that carry financial, compliance or operational consequences.

OB360 designs agentic systems that act within defined business, data and security boundaries. Work can involve one agent or several specialized agents, each with explicit responsibilities, approved tools, state management and escalation paths. Human approvals are retained where an action carries financial, compliance or operational consequences. Evaluation and observability are considered alongside orchestration.

Problems

Designed around your business

  • Architecture before tools

    We define the business workflow, constraints and right level of AI before choosing implementation patterns.

  • Engineering accountability

    Our work spans concept, integration, software delivery and handover.

  • Controlled enterprise AI

    We design with boundaries, permissions, human review and evaluation in mind.

  • Specialist depth

    Agents, graph intelligence, document AI, applied ML and cloud-native engineering can be combined when the problem requires them.

Who it is for

Where this service fits

This service fits processes that need several steps, several systems and several people to reach one outcome.
  • Enterprise leaders planning practical AI adoption.
  • Software and product teams extending existing applications.
  • Business and engineering teams connecting workflows, knowledge and systems.

Use cases

An illustrative business scenario

  • A possible engagement

    A complex exception-handling workflow requires information retrieval, rule interpretation, stakeholder follow-up and preparation of a decision for human review. Different agents can collaborate while critical decisions stay under authorized human control.

Related case studies

Approach

From requirements to delivery

Each engagement moves through four stages.

  1. Understand

    Agree the business problem, users, existing systems and constraints.

  2. Design

    Choose the architecture, data boundaries and appropriate human oversight.

  3. Engineer

    Implement the agreed scope with testing and integration.

  4. Enable

    Share implementation knowledge and agree operational next steps.

Technology

Typical scope

A typical engagement can cover the following areas.
  • Agent and tool boundaries
  • Orchestration patterns
  • Business system integrations
  • Retrieval/memory strategies
  • Approvals and guardrails
  • Observability, evaluation and AgentOps

Delivery

Delivery model

Engagement scope, team structure and delivery priorities are agreed around your business needs.

Specific deliverables and implementation boundaries depend on the agreed engagement.

What to expect from an engagement

Agent and tool specification, orchestration design, integration components, approval workflows, testing, and operational monitoring approach.

Questions

Questions about this service

Why not let the agent automate everything?

The right level of autonomy depends on the consequences of an error. Important financial, regulated or irreversible actions often need policy checks and human approval.

Can this work connect to our existing software?

OB360 can integrate AI capabilities with existing applications, data and APIs, with access boundaries defined for the engagement.

How do we start?

Discuss your workflow and constraints with OB360 to agree the relevant discovery and engineering scope.

What is a multi-agent system?

A multi-agent system divides a business process among several specialized AI agents that coordinate with one another, each with its own responsibilities, tools and permissions. A coordinating hub routes work and combines the results.

Has OB360 delivered a multi-agent system?

Yes. OB360 delivered a multi-agent business intelligence assistant in which a central hub coordinates product, inventory and portfolio agents inside Microsoft Teams. OB360 has also published a reference architecture for multi-agent billing exception management.

Next steps

Related services

Explore complementary consulting and engineering services for your initiative.

Discuss a Multi-Agent Solution

Tell us about your business workflow, users and existing systems. We will discuss the architecture, engineering support and next steps that fit your needs.

Discuss your AI initiativebusiness@onboard360.com